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Computational Postdoctoral Fellow (Quantitative Modeling Group) - 106785 Division: BE-Biological Systems & Engineering Berkeley Lab’s (LBNL, https://www.lbl.gov/) Biological Systems and Engineering
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Develop theoretical models of topological materials to understand & interpret experimental data Leverage nanofabrication facilities & collaborate with other leading research groups at the School
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qualitative and quantitative methods. You will have some experience in mathematical modelling and basic-level programming. But our main requirement is for someone who will understand the plant and soil science
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of previously published information geological restorations and basin modelling to improve the understanding of the interplay between tectonic and sedimentary processes, particularly where salt is present
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5 Aug 2026 Job Information Organisation/Company INESC TEC Research Field Computer science » Informatics Engineering » Electrical engineering Mathematics » Applied mathematics Researcher Profile
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project. · Architect and evaluate multi-site cardiotoxicity risk prediction models integrating structured EHRs, clinical notes via natural language processing, strain echocardiography features, and
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into practical systems. Key Responsibilities Derive and analyse closed-form mathematical expressions for latency and offloading probabilities across edge-only, cloud-only, and edge-cloud computation offloading
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the assembly, management, and analysis of complex datasets, including the application of machine learning techniques to develop a range of models such as predictive and image-recognition models. A key aspect of
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. Qualifications The proposed project extensively involves mathematical modelling, computer programming, numerical simulation and experimental investigation of two-phase flows. It requires researchers to have PhD
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30th September 2026 Languages English English Norsk Nynorsk English PhD Research Fellow in climate data analysis and machine learning emulation of hydrological models Apply for this job See